Definition of Spring cloud stream
Spring cloud stream is also a framework which helps us to create and build the message-driven and event-driven microservices for the application, this framework is built on top of existing frameworks like spring boot and spring integration. By the use of it, we can build a very highly scalable microservices system that will be connected by the messaging systems, spring cloud stream implements on the base of some core fundamentals, which are known as the building block of spring cloud stream. In the coming section of the tutorial, we will have a closer look at the implementation, each and every detail about the framework which will help us to understand it better for usage in application.
Why do we need spring cloud stream?
In practice Senecio we always want our application to be flexible and scalable, so spring cloud stream is a framework that provides highly scalable microservices for the application, also it is based on the existing framework only to easy and familiar to use and start work with it. It has so many binder implementations which makes it a good choice to use this in application some of them are described below let’s get started;
1) RabbitMQ and Apache Kafka: Both these are the messaging application, these are used to transmit the stream of a message to the producer and the consumer, so they both support the pub-sub mechanism which is easy to use if we have this required or we have lots of data which is going to be received by the flowing stream.
If we talk about the RabbitMQ in detail so it is often known as the message broker, which helps us to push the messages from the service to the consumer, i.e. from producer to consumer in short. On the other hand, we have Apache Kafka, this internally uses a hybrid model, which is consists of two things is the combination i.e. message queuing and pub-sub concept, this also allows and supports us to distribute the processing in the application.
2) Amazon Kinesis: The second thing it supports the binder implementation is the Amazon Kinesis, this is a service that allows us to process a large amount of data per second it is very scalable. manageable, and helps for real-time processing of the stream. This allows us the developers to take any amount of data from any source which can either be single or multiple sources and run on EC2 instances. This binder implementation of spring cloud stream can be used in the following mentioned points see below;
a) Real-time graphs
b) Data log and data feed intake
c) Real-time data analytics
3) Google PubSub: This binder implementation of the spring stream allows us to process the stream of messages, this also based on the consumer and publisher concept hence known as PubSub, it does the same things for us to receive and consumer message from the Google PubSub.
4) Azure Event Hubs: As the name suggests it is an event streaming platform by the use of it we can easily process millions of events. We can send data by the use of this event hub and that can be stored by the batch adapters or analytics provider. Below are some points where we can t=use this binder implementation from the spring stream cloud which are mentioned below;
a) Device telemetry streaming
b) Archiving data
c) Anomaly detection (fraud/outliers)
d) Analytics pipelines, such as clickstreams
e) Transaction processing
f) User telemetry processing
g) Live dashboarding
h) Application logging
How does Spring cloud stream work?
As of now we already know that it is basically used to process the stream of messages and build highly scalable microservices that are connected. We have already seen its binder implementation which can be used with the spring cloud stream. This is a framework that is built on the extension of the existing framework like spring boot and spring integration. In this section, we will see how it works internally what is the fundamental blocks it uses to implementation this stream processing of messages let’s get started.
In spring cloud stream uses the building block as the core concept behind it, basically, it uses three build blocks which are as follows;
1) Message: This is the message we want to send and receive based on the pub-sub mechanism. This message allows the consumer and the producer to be able to communicate with the destination.
2) Destination Binders: This is the core building block for this which is responsible to support and provide the integration with the external system or external messaging system we have.
3) Destination Bindings: This building block act as the bridge between the two components which want to communicate and want to exchange messages. The one is an external system and the application code itself, hence in short it acts as a bridge between the application and external messaging systems which is going to send us the messages.
This is simply based on the producer’s concept which allows us to consume and produce the messages between the two application systems.
Advantages and Disadvantages
It has so many advantages out of which few are mentioned below;
- It allows us to create a highly scalable system for the application
- Support back pressure
- ability to scale up any portion of the application
- Maximization of throughput
We cannot say any disadvantages but it has one limitation with it;
- It just prevents the testing for the logic that is specific to the binder implementation.
As we have seen that this spring cloud stream is highly scalable and by the use of it we can easily process millions or thousands of stream data per second. Easy to implement and use as well, we can find much support for this online. But we should first have a spring boot application with all the necessary dependencies added in the build file to be able to use this.
This is a guide to the Spring cloud stream. Here we discuss definition, syntax, and parameters, Why do we need a spring cloud stream? examples with code implementation. You may also have a look at the following articles to learn more –